Upskill yourself in Data Science + AI With Live Classes From Industry Experts.

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Data Analytics | AI
Deep Learning | ML

The Next Batch Starts from June

Start Your Tech Journey Now!!

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Acquire industry-valued skills

Practice Based Learning

Get skilled in Today's most demanded skillset in the Industry and future proof your career by solving case studies under the guidance of industry experts.

Chat GPT
Deep Learning
Machine Learning
Power BI

Why Choose Digikull?

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Get trained by experts ask doubts in the live session.Evening classes on Fri, Sat & Sunday

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Having an issue? Ask doubts from your mentors any time during office hours.

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Ask for Personal mentorship in case you need guidance at any time during your program.

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Solve practical problems in Practice sessions under the guidance of your mentors.

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Facing a live interview needs a lot of practice. unlimited mock interviews on the Digikull tech platform.

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college-like placements with Digikull recruitment partners.Help with soft skills, resume preparation & lot more until you get placed.

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Pause your course and restart a month later with the next batch!

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Build and highlight Industry level Projects in your resume.

Interview Tool

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Watch the recording later, with teaching assistants available to solve your doubts.


Pause your course and restart a month later with the next batch!


Access assignments/notes lifelong and recordings upto 6 months post course completion.


Get them resolved over text / video by our expert students success team !

Course Curriculum

Syllabus Data Science + AI course

24 Weeks

  • Variable, Expressions, And Statement
  • Functions, Iterations, Strings
  • Conditionals And Loops
  • Lists, Dictionaries, Tuples
  • File Handling And Operations
  • OOPS
  • Data Visualization
  • Data Manipulation With NUMPY
  • Data Analysis With PANDAS
  • Lists, Dictionaries, Tuples
  • Matplotlib & Seaborn
  • Speed Up File Loading
  • Reduce Memory Usage
  • SpeedUp Column Operations
  • Optimise Data Filtering

  • Introduction to MYSQL
  • MYSQL Installation
  • Getting Started with SQL and Queries
  • Queries with Constraints
  • DDL Statements, DDL Statements
  • Joins in SQL
  • Queries with Aggregates
  • Analytical Function
  • Database Design
  • MYSQL Procedural Extension
  • Transaction Control
  • Query Performance

  • Introduction to Power BI
  • Data Cleaning in Power Query Editor
  • Menu Tab in Power Query Editor
  • Advance Function in Power Query Editor
  • Introduction to Power BI Desktop
  • Power BI Desktop Menu Tab
  • Measures in Power BI
  • Insert Menu
  • Data Visualization
  • Charts, Maps, Tables and Its Types
  • Introduction to DAX Function
  • DAX and Measures
  • Basics of M Language and Bookmark
  • Create a Dashboard
  • Create Filters on the Dashboard
  • Dashboard Objects
  • Create a Stroy
+20 Weeks

  • Basis of Statistics
  • Types of Data, Introduction of Data Gathering, Describing Data
  • Making Conclusion,Prediction, Parameters
  • Sample and Sample Tpye
  • Measurement Level
  • Frequency Table
  • Tendency and Distribution of Table
  • Mode, Median Mean , Variance, Standard Deviation
  • .Covariance Correlation
  • Range, Quartile and Percentile
  • Statistics Inference & Distribution
  • Distribution and its Types
  • Distribution & Estimation
  • Proportion Estimation
  • Mean Estimation
  • Confidence Intervals
  • A/B Testing
  • Null and Alternative Hypothesis
  • Type 1 & Type 2 Error
  • Statistical Test (Student's T-Test, F-Test, Z-Test )
  • Chi-Square Test, Annova Test, Binomial Test & Sample Median Test
  • Testing Proportion and Testing Mean

  • Introduction to Machine learning
  • Data Science life cycle & Data Cleaning
  • Feature Engineering & Linear Regression
  • linear Regression in OLS Method
  • Logistic Method
  • Decision Tree & Random Forest
  • Boosting Alogo (ADABOOST & XB BOOST )
  • Support Vector Machine (SVM)
  • Naive Bayes, KNN, K Means
  • Hierarchical Clustering
  • Scikit Learn
  • Tensorflow
  • Data Analysis With PANDAS
  • Lists, Dictionaries, Tuples
  • Matplotlib & Seaborn

  • Introduction to Neural Networks
  • Introduction to Activation functions
  • Sigmoid and Tanh Activation Functions
  • Relu, and Leaky Relu, Activation Functions
  • When to use Sigmoid and Softmax
  • Introduction to Gradient Descent
  • Batch vs Stochastic Gradient Descent
  • Introduction to Optimizers
  • Dropout and why do we need it
  • Hyper parameter Tuning in Neural Networks
  • Introduction to Batch Normalization
  • Introduction to Tensorflow 2.0 Part 1
  • Implementing a basic neural network
  • Improving a Neural network
  • Convolution Operation in CNN
  • Padding and Pooling
  • Data Augmentation
  • Understanding CNN end to end
  • Implementing Data Processing on Image Data
  • Implementing CNN using Tensorflow
  • Introduction to CNN Architectures
  • Introduction to Transfer Learning
  • Implementing ResNet and Inception Network
  • Industry relevance
  • Introduction to RNN
  • Implementing RNN using Tensorflow
  • Vanishing and Exploding Gradients
  • Introduction to LSTMs
  • Implementing GRU and LSTM using Tensorflow
  • Introduction to Bidirectional Networks
  • Implementing BIGRU and BILSTM
  • Industry relevance of RNNs

  • Derive insights from the data, create report
  • Intro into Google Colab
  • Key Prompt Engineering Principles for Mastering ChatGPT
  • Data Preparation Techniques for Improved Decision-Making
  • Use ChatGPT to Prepare Data
  • Mastering Categorical Data Encoding with ChatGPT for Data Analytics
  • Descriptive Data Analysis for Deriving Business Insights
  • Iterative Feature Engineering with ChatGPT and Python
  • Feature Creation using ChatGPT: Decoding data
  • ChatGPT as a Co-Pilot in Exploratory Data Analysis and Simplifying Insights
  • Streamlining Qualitative Data Analysis using ChatGPT: Text Categorization
  • Using ChatGPT for Text Classification: A Deep Dive into Sentiment Analysis
  • Creating Data Analysis Reports and Communicating

Download our curriculum to explore the course structure, detailed lesson plans, and learning outcomes. Get ready to unlock the power of data and take your career to new heights!

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Course Certification

Digikull Certification

The Digikull AI course is highly esteemed within the corporate sphere, ensuring our graduates uphold exceptional quality. The certification from Digikull's AI course holds significant value for companies due to its alignment with industry standards. Students undergo rigorous training for Eight months, which involves minimum of five capstone product development before earning the certification. The AI course certification is exclusively awarded to students who successfully complete the program.

check mark Complete all assignments.

check markBuild 5 Capstone Projects

check mark Clear the final day test by the Digikull.

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Celebrate DigiKull‘s achievements as it shines in the spotlight, garnering recognition for its outstanding accomplishments.

Frequently Asked Questions

Got a Question ? We are here to Answer!!

What are the eligibility criteria to apply for Digikull's programs?


Quality education is not a privilege, it's a fundamental human right. Every individual, regardless of their background or circumstances, deserves access to the transformative power of learning.

    What is the duration of the program?


    The duration of our program typically ranges from 5 to 7 months, depending on the specific program you choose to pursue. You can visit our courses page to get exact duration of course.

      Does Digikull provide interview preparation support?


      Absolutely! At Digikull, we offer comprehensive interview preparation assistance. Our dedicated placement team will guide you in crafting a compelling resume, optimizing your LinkedIn profile, and conducting unlimited mock interviews to help you ace your job interviews.

        Can I enroll in Digikull's courses without any coding experience?


        Absolutely! Our courses are specifically designed to accommodate learners with no prior coding experience. By attending all the classes and following our carefully crafted curriculum, you'll be guided step-by-step to master the art of coding.

        When does the placement process begin and what is the procedure?


        The placement process at Digikull commences after 5 months of your enrollment in the course. Once you have acquired the necessary skills and completed prior modules, you can start applying to companies that align with your eligibility and skillset

        Am I required to accept a job offer provided by Digikull?


        We value your preferences and seek your interest before referring you to a particular company. However, once you accept an interview or receive an offer through our platform, rejecting further interviews or declining the offer violates the trust we have placed in you. In such cases, the ISA (Income Share Agreement) will be initiated based on the offer received.